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The molecular mechanisms of angiogenesis have been intensely studied, but many genes that control endothelial behavior and fate still need to be described. Here, we characterize the role of Apold1 (Apolipoprotein L domain containing 1) in angiogenesis in vivo and in vitro. Single-cell analyses reveal that - across tissues - the expression of Apold1 is restricted to the vasculature and that Apold1 expression in endothelial cells (ECs) is highly sensitive to environmental factors. Using Apold1$^{-/-}$ mice, we find that Apold1 is dispensable for development and does not affect postnatal retinal angiogenesis nor alters the vascular network in adult brain and muscle. However, when exposed to ischemic conditions following photothrombotic stroke as well as femoral artery ligation, Apold1$^{-/-}$ mice display dramatic impairments in recovery and revascularization. We also find that human tumor endothelial cells express strikingly higher levels of Apold1 and that Apold1 deletion in mice stunts the growth of subcutaneous B16 melanoma tumors, which have smaller and poorly perfused vessels. Mechanistically, Apold1 is activated in ECs upon growth factor stimulation as well as in hypoxia, and Apold1 intrinsically controls EC proliferation but not migration. Our data demonstrate that Apold1 is a key regulator of angiogenesis in pathological settings, whereas it does not affect developmental angiogenesis, thus making it a promising candidate for clinical investigation.

The quantification of behaviors of interest from video data is commonly used to study brain function, the effects of pharmacological interventions, and genetic alterations. Existing approaches lack the capability to analyze the behavior of groups of animals in complex environments. We present a novel deep learning architecture for classifying individual and social animal behavior, even in complex environments directly from raw video frames, while requiring no intervention after initial human supervision. Our behavioral classifier is embedded in a pipeline (SIPEC) that performs segmentation, identification, pose-estimation, and classification of complex behavior, outperforming the state of the art. SIPEC successfully recognizes multiple behaviors of freely moving individual mice as well as socially interacting non-human primates in 3D, using data only from simple mono-vision cameras in home-cage setups.

The acute stress response mobilizes energy to meet situational demands and re-establish homeostasis. However, the underlying molecular cascades are unclear. Here, we use a brief swim exposure to trigger an acute stress response in mice, which transiently increases anxiety, without leading to lasting maladaptive changes. Using multiomic profiling, such as proteomics, phospho-proteomics, bulk mRNA-, single-nuclei mRNA-, small RNA-, and TRAP-sequencing, we characterize the acute stress-induced molecular events in the mouse hippocampus over time. Our results show the complexity and specificity of the response to acute stress, highlighting both the widespread changes in protein phosphorylation and gene transcription, and tightly regulated protein translation. The observed molecular events resolve efficiently within four hours after initiation of stress. We include an interactive app to explore the data, providing a molecular resource that can help us understand how acute stress impacts brain function in response to stress.

Chronic stress exposure in adolescence can lead to a lasting change in stress responsiveness later in life and is associated with increased mental health issues in adulthood. Here we investigate whether the Chronic Social Instability (CSI) paradigm influences the behavioral and molecular responses to novel acute stressors in mice, and whether it alters physiological responses influenced by the noradrenergic system. Using large cohorts of mice, we show that CSI mice display a persistent increase in exploratory behaviors in the open field test alongside small but widespread transcriptional changes in the ventral hippocampus. However, both the transcriptomic and behavioral responses to novel acute stressors are indistinguishable between groups. In addition, the pupillometric response to a tail shock, known to be mediated by the noradrenergic system, remains unaltered in CSI mice. Ultra-high performance liquid chromatography analysis of monoaminergic neurotransmitter levels in the ventral hippocampus also shows no differences between control or CSI mice at baseline or in response to acute stress. We conclude that CSI exposure during adolescence leads to persistent changes in exploratory behavior and gene expression in the hippocampus, but it does not alter the response to acute stress in adulthood and is unlikely to alter the function of the noradrenergic system.

Analysing the behavior of individuals or groups of animals in complex environments is an important, yet difficult computer vision task. Here we present a novel deep learning architecture for classifying animal behavior and demonstrate how this end-to-end approach can significantly outperform pose estimation-based approaches, whilst requiring no intervention after minimal training. Our behavioral classifier is embedded in a first-of-its-kind pipeline (SIPEC) which performs segmentation, identification, pose-estimation and classification of behavior all automatically. SIPEC successfully recognizes multiple behaviors of freely moving mice as well as socially interacting nonhuman primates in 3D, using data only from simple mono-vision cameras in home-cage setups.

The hippocampal formation is a brain structure essential for higher-order cognitive functions. It has a complex anatomical organization and cellular composition, and hippocampal subregions have different properties and functional roles. In this study, we used SWATH-MS to determine whether the proteomes of hippocampus areas CA1 and CA3 can explain the commonalities or specificities of these subregions in basal conditions and after recognition memory. We show that the proteomes of areas CA1 and CA3 are largely different in basal conditions and that differential changes and dynamics in protein expression are induced in these areas after recognition of an object or object location. While changes are consistent across both recognition paradigms in area CA1, they are not in area CA3, suggesting distinct proteomic responses in areas CA1 and CA3 for memory formation.